An Analysis of the Effects of Neighborhood Size and Shape on Local Selection Algorithms
PPSN IV Proceedings of the 4th International Conference on Parallel Problem Solving from Nature
Takeover time curves in random and small-world structured populations
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
The Structure and Dynamics of Networks: (Princeton Studies in Complexity)
The Structure and Dynamics of Networks: (Princeton Studies in Complexity)
An analysis of the effects of population structure on scalable multiobjective optimization problems
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Dynamical Processes on Complex Networks
Dynamical Processes on Complex Networks
Evolutionary dynamics on scale-free interaction networks
IEEE Transactions on Evolutionary Computation
Multiobjective evolutionary algorithms on complex networks
EMO'07 Proceedings of the 4th international conference on Evolutionary multi-criterion optimization
Genetic algorithms on NK-landscapes: effects of selection, drift, mutation, and recombination
EvoWorkshops'03 Proceedings of the 2003 international conference on Applications of evolutionary computing
Effects of scale-free and small-world topologies on binary coded self-adaptive CEA
EvoCOP'06 Proceedings of the 6th European conference on Evolutionary Computation in Combinatorial Optimization
The exploration/exploitation tradeoff in dynamic cellular genetic algorithms
IEEE Transactions on Evolutionary Computation
Selection intensity in cellular evolutionary algorithms for regular lattices
IEEE Transactions on Evolutionary Computation
The Self-Organization of Interaction Networks for Nature-Inspired Optimization
IEEE Transactions on Evolutionary Computation
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We build on recent advances in the design of self-organizing interaction networks by introducing a sexual variant of an existing asexual, mutation-limited algorithm. Both the asexual and sexual variants are tested on benchmark optimization problems with varying levels of problem difficulty, deception, and epistasis. Specifically, we investigate algorithm performance on Massively Multimodal Deceptive Problems and NK Landscapes. In the former case, we find that sexual recombination improves solution quality for all problem instances considered; in the latter case, sexual recombination is not found to offer any significant improvement. We conclude that sexual recombination in self-organizing interaction networks may improve solution quality in problem domains with deception, and discuss directions for future research.